Core Research Software Engineer I - Integrated Genomics Core

Salk Institute Office of Technology Development•San Diego, CA

21h•$33 - $38

About The Position

The Salk Institute Core Facilities generate, manage, and compute against large-scale datasets across genome sequencing, gene expression profiling, microscopy, spatial imaging, flow cytometry, and mass spectrometry. The Core Facilities seek a Research Software Engineer to support daily systems administration and operations for the technology infrastructure underlying data- and compute-intensive research resources and administrative services. The role includes managing servers, storage, instruments, and user services, with a focus on configuring, monitoring, and maintaining systems so they remain secure, reliable, and performant. Under the general supervision of the Director of the Integrative Genomics Core, the Research Software Engineer works with Salk Institute IT and Center for AI and Research Computing personnel to support Core staff in implementing hardware and software solutions and maintaining complex systems. The position bridges research and software engineering, working directly with scientists to translate evolving research needs into practical tools and services. It contributes to Salk’s scientific mission by maintaining robust Core Facilities services in a collaborative, mission-driven environment.

Requirements

A BS degree in computer science, engineering, quantitative science, or a related discipline is preferred.
Strong proficiency in Linux server administration, such as Red Hat/CentOS or Ubuntu Linux, including shell scripting and command-line tools.
Strong analytical and troubleshooting skills, including the ability to methodically isolate root causes in complex environments.
Excellent verbal and written communication skills, including documenting processes and explaining technical issues to non-technical audiences.
A customer-service-oriented attitude when working with researchers and staff.
Ability to work independently and collaboratively, manage time effectively, and handle multiple tasks.
Full-stack software engineering ability, including Python and at least one other programming language, and experience building applications spanning back-end logic, front-end interfaces, and data storage.
Fluency with modern AI-assisted software development, including effective use of AI coding tools and large language models to design, build, debug, and ship software.
Ability to learn unfamiliar systems and technologies quickly and establish working services and pipelines through code, scripting, and automation.
Comfort working in Linux/Unix environments with Git, testing, and code review.

Nice To Haves

A master’s degree or post-baccalaureate certification in a computational or scientific field.
Prior internship, research, or work experience in a scientific, laboratory, or academic environment.
Full-stack web development experience with modern frameworks such as React, Svelte, Vue, FastAPI, or Django.
Experience integrating software with scientific instruments or hardware, such as cameras, scanners, or data-acquisition devices.
Experience with containerization such as Docker and scheduling work on GPU resources such as Kubernetes or SLURM; high-performance computing or systems-administration experience is welcome.
Experience deploying and maintaining self-hosted applications and services, including on cloud platforms such as AWS or GCP.
Experience maintaining an open-source software project, including packaging, releases, and responding to community issues.
Academic coursework, research experience, or demonstrated interest in plant science, biology, neuroscience, or another life-science domain.
A track record of independently shipping small tools or projects quickly and learning new languages, frameworks, and systems with minimal ramp-up.
Strong communication skills and ability to work directly with scientists to translate their needs into technical solutions.
A public code portfolio, such as GitHub, demonstrating initiative beyond coursework through personal projects or open-source contributions.

Responsibilities

Develop, maintain, and release open-source scientific packages for core research, using professional software engineering practices such as Git, code review, testing, type checking, and CI/CD.
Support and use shared high-performance computing resources, including GPU cluster scheduling and containerized job workflows such as Kubernetes-based schedulers and SLURM.
Rapidly prototype, build, and iterate on internal applications, command-line tools, and utilities in response to scientific needs.
Integrate systems and services through APIs, authentication, and automation to create seamless user workflows.
Work directly with biologists and other scientists to understand experimental goals and translate them into technical solutions.
Prepare and maintain documentation, runbooks, and training materials to help researchers use tools and pipelines independently.
Contribute to the lab’s open-source software community by reviewing external contributions and responding to user issues.
Participate in project planning and status discussions, coordinating with other Salk labs, Core Facilities, and programs.
Monitor and maintain Core Facilities system health and capacity, supporting service reliability and uptime.
Install and configure operating systems, primarily Linux/Unix and Windows, on servers, workstations, and other Core Facility devices; apply patches and updates.
Execute backup and restore procedures, monitor on-premises and cloud backup jobs, and remediate failures.
Monitor on-premises and cloud storage usage and address routine storage, performance, and reliability issues.
Respond promptly to operational issues, documenting resolutions and follow-up actions for team knowledge sharing.
Identify and recommend improvements to system reliability, performance, and efficiency, and contribute to Core Facility initiatives using automation and other practices.
Perform other related duties as assigned, including possible inventory management, procedure documentation, training, or cross-training.